cm013 Exercise

Saving Graphs to File

• Don’t use the mouse
• Use ggsave for ggplot
  • Practice by saving the following plot to file:

p <- ggplot(mtcars, aes(hp, wt)) + 
    geom_point()
ggsave("plot.png", p)

Saving 7 x 7 in image

• Base R way: print plots “to screen”, sandwiched between pdf()/jpeg()/png()… and dev.off().
• Vector vs. raster: Images are stored on your computer as either vector or raster.
  • Raster: an n by m grid of pixels, each with its own colour. jpeg, png, gif, bmp.
  • Vector: represented as shapes and lines. pdf, svg.
  • For tips: “10 tips for making your R graphics look their best”“.

Scales; Colour

Scale functions in ggplot2 take the form scale_[aesthetic]_[mapping]().

Let’s first focus on the following plot:

1. Change the y-axis tick mark spacing to 10; change the colour spacing to include all powers of 10.

2. Specify scales::*_format in the labels argument of a scale function to do the following:
   • Change the x-axis labels to dollar format (use scales::dollar_format())
   • Change the colour labels to comma format (use scales::comma_format())

3. Use RColorBrewer to change the colour scheme.
   • Notice the three different types of scales: sequential, diverging, and continuous.

4. Use viridis to change the colour to a colour-blind friendly scheme
   • Hint: add scale_colour_viridis_c (c stands for continuous; d discrete).
   • You can choose a palette with option.

Theming

Changing the look of a graphic can be achieved through the theme() layer.

There are “complete themes” that come with ggplot2, my favourite being theme_bw (I’ve grown tired of the default gray background, so theme_bw is refreshing).

1. Change the theme of the following plot to theme_bw():

2. Then, change font size of axis labels, and the strip background colour. Others?

Plotly

Consider the following plot:

1. Convert it to a plotly object by applying the ggplotly() function:

2. You can save a plotly graph locally as an html file. Try saving the above:
   • NOTE: plotly graphs don’t seem to show up in Rmd notebooks, but they do with Rmd documents.

p %>% 
    ggplotly() %>% 
    htmlwidgets::saveWidget("LOCATION_GOES_HERE")

3. Run this code to see the json format underneath:

    ggplotly() %>% 
    plotly_json()

Error: Package `listviewer` required for `plotly_json`.
Please install and try again.

4. Check out code to make a plotly object from scratch using plot_ly() – scatterplot of gdpPercap vs lifeExp.
   • Check out the cheat sheet.

5. Add population to form a z-axis for a 3D plot: